Incompatibility with ExplainableBoostingRegressor: unsupported feature type 'ordinal'

[zuberman35]

After training an EBM Regressor and manually specifying the datatypes to 'nominal or 'ordinal' ( as categorical is not supported) I cannot create a gc, even when manually trying to change the feature_types. See below example for the MPG dataset.

ebm = ExplainableBoostingRegressor(
    feature_names=['displacement', 'horsepower', 'weight', 'acceleration','origin', 'cylinders', 'model_year'
       ],
    feature_types=['continuous', 'continuous','continuous','continuous','nominal','ordinal','ordinal'],
    random_state=42,
    n_jobs=-1
)
ebm.fit(X_train, y_train)
ebm.feature_types = ['continuous', 'continuous', 'continuous', 'continuous', 'categorical', 'categorical', 'categorical']

gc only seems to work with feature_type='none'.

Is there a workaround or fix?

[paulbkoch]

To hack this, try this instead (NOTE: I have not tested this):

ebm.feature_types_in_ = ['continuous', 'continuous', 'continuous', 'continuous', 'categorical', 'categorical', 'categorical']

[paulbkoch]

Actually, looking at the code I think it will instead need to be:

ebm.feature_types_in_ = ['continuous', 'continuous', 'continuous', 'continuous', 'nominal', 'nominal', 'nominal']

Because here 'nominal' is supported, but not 'categorical' or 'ordinal'. For prediction 'nominal' and 'ordinal' will be identical:

https://github.com/interpretml/gam-changer/blob/aba94f624c726e63ef7360c5c691aedac3a44bd4/notebook-widget/gamchanger/gamchanger.py#L64

https://github.com/interpretml/gam-changer/blob/aba94f624c726e63ef7360c5c691aedac3a44bd4/notebook-widget/gamchanger/gamchanger.py#L84

[zuberman35]

This worked, thanks for the lightning fast response :)

[zuberman35]

While this fix works in a sense, that it displays the gc visual, the metrics (right) are now gone, see below screenshot

[paulbkoch]

Two questions:

1. If you train the model using only nominals (no ordinals), does it still have this visualization issue. My guess is that it will.
2. What datatypes are the columns of X? If you force the nominal and ordinal columns to be strings, does that fix the issue?